Hi everyone,
I want to solve equations of the form Ax = b or Ax = B where A is a
dense symmetric positive definite matrix. I want to be able to support
potentially large A so I find it convenient to store A as a 1d-vector
containing the upper part of the matrix only. It's easy to convert
this 1d representation to a 2d-representation, and vice-versa.
I believe functions like linalg.solve (when passed sym_pos=True) and
linalg.cholesky would benefit from accepting 1d-arrays of this kind.
Is there a memory efficient way of solving my equations for a large A?
Thanks,
Mathieu